Data Science For Dummies
(eAudiobook)

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Published
Tantor Media, Inc., 2019.
Status
Available Online

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Physical Description
10h 29m 0s
Format
eAudiobook
Language
English
ISBN
9781515936770

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Citations

APA Citation, 7th Edition (style guide)

Lillian Pierson, P. E., Lillian Pierson, P. E., & Chloe Cannon|READER. (2019). Data Science For Dummies . Tantor Media, Inc..

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Lillian Pierson, P. E, P. E.|AUTHOR Lillian Pierson and Chloe Cannon|READER. 2019. Data Science For Dummies. Tantor Media, Inc.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Lillian Pierson, P. E, P. E.|AUTHOR Lillian Pierson and Chloe Cannon|READER. Data Science For Dummies Tantor Media, Inc, 2019.

MLA Citation, 9th Edition (style guide)

Lillian Pierson, P. E., P. E.|AUTHOR Lillian Pierson, and Chloe Cannon|READER. Data Science For Dummies Tantor Media, Inc., 2019.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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Grouped Work IDacc647df-750e-a268-937d-609f7fb92825-eng
Full titledata science for dummies
Authore lillian pierson p
Grouping Categorybook
Last Update2023-01-14 19:02:10PM
Last Indexed2024-03-27 02:35:53AM

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    [synopsis] => Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. Data Science For Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, listening to this book will help you understand what technologies, programming languages, and mathematical methods on which to focus.

While this book serves as a wildly fantastic guide through the broad, sometimes intimidating field of big data and data science, it is not an instruction manual for hands-on implementation. Here's what to expect:

• Provides a background in big data and data engineering before moving on to data science and how it's applied to generate value.

• Includes coverage of big data frameworks like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL.

• And more.

It's a big, big data world out there-let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.
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